| policy: |
| name: acp |
| _target_: force_il.policies.acp.ACPPolicy |
| action_dim: 19 |
| pred_horizon: 16 |
| obs_horizon: 2 |
| action_horizon: 16 |
| vision_encoder_name: vit_base_patch32_clip_224.openai |
| vision_pretrained: true |
| vision_output_dim: 768 |
| wrench_encoding: causalconv |
| wrench_window_size: 256 |
| wrench_freq: 5000.0 |
| wrench_output_dim: 384 |
| fuse_mode: modality-attention |
| obs_num_rgb_frames: 2 |
| include_low_dim: true |
| low_dim_eef_pos_horizon: 3 |
| low_dim_eef_pos_dim: 3 |
| low_dim_eef_rot_horizon: 3 |
| low_dim_eef_rot_dim: 6 |
| num_diffusion_steps: 50 |
| noise_scheduler: ddim |
| unet_down_dims: |
| - 256 |
| - 512 |
| - 1024 |
| diffusion_step_embed_dim: 32 |
| unet_kernel_size: 5 |
| unet_n_groups: 8 |
| cond_predict_scale: true |
| input_perturbation: 0.1 |
| unified_action: true |
| unified_action_dim: 19 |
| pose_dim: 9 |
| vt_dim: 9 |
| stiffness_dim: 1 |
| predict_virtual_target: false |
| predict_stiffness: false |
| default_stiffness: 100.0 |
| num_inference_steps: 16 |
| task: |
| name: flip_up |
| dataset_path: data/flip_up_230/flip_up_new_v5 |
| action_dim: 19 |
| obs_horizon: 2 |
| eef_obs_horizon: 3 |
| eef_down_sample_steps: 5 |
| pred_horizon: 16 |
| action_horizon: 16 |
| action_down_sample_steps: 50 |
| wrench_horizon: 32 |
| wrench_down_sample_steps: 4 |
| query_down_sample_steps: 8 |
| image_size: 224 |
| val_ratio: 0.05 |
| data: |
| _target_: force_il.data.acp_dataset.ACPEpisodeDataset |
| dataset_path: data/flip-20e_acp |
| pred_horizon: 16 |
| obs_horizon: 2 |
| rgb_down_sample_steps: 10 |
| eef_obs_horizon: 3 |
| eef_down_sample_steps: 5 |
| action_down_sample_steps: 50 |
| wrench_horizon: 32 |
| wrench_down_sample_steps: 4 |
| query_down_sample_steps: 8 |
| image_size: 224 |
| val_ratio: 0.05 |
| seed: 42 |
| is_val: false |
| relative_actions: true |
| train: |
| epochs: 300 |
| batch_size: 128 |
| gradient_accumulation: 1 |
| optimizer: |
| _target_: torch.optim.AdamW |
| lr: 0.0003 |
| weight_decay: 1.0e-06 |
| betas: |
| - 0.95 |
| - 0.999 |
| scheduler: |
| type: cosine |
| warmup_steps: 2000 |
| min_lr: 1.0e-06 |
| encoder_lr_scale: 0.1 |
| mixed_precision: fp16 |
| use_ema: true |
| ema_decay: 0.9999 |
| ema_power: 0.75 |
| ema_update_after_step: 0 |
| log_interval: 50 |
| use_wandb: true |
| wandb_project: force_il |
| wandb_name: null |
| val_every: 5 |
| sample_every: 5 |
| val_interval: 500 |
| checkpoint_interval: 10 |
| save_best: true |
| best_checkpoint_monitor: train_loss |
| num_workers: 8 |
| pin_memory: true |
| prefetch_factor: 2 |
| normalizer_use_full_dataset: false |
| upload_to_hf: true |
| hf_repo_id: tangPR/acp-flip-up |
| hf_upload_interval: 100 |
| seed: 42 |
| experiment_name: acp_flip_up |
| seed: 42 |
| validate: |
| checkpoint: null |
| num_samples: 5 |
| output_dir: ./validation_plots |
| use_train_split: false |
| output_dir: outputs/2026-03-23/acp_flip_up_205858 |
| checkpoint_dir: outputs/2026-03-23/acp_flip_up_205858/checkpoints |
| log_dir: outputs/2026-03-23/acp_flip_up_205858/logs |
|
|
